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zoharbabin

Google Researcher MCP

Google Image Search

google_image_search
Read-only

Retrieve images matching specific criteria using Google Custom Search. Filter by size, type, color, and format to find photos, clipart, or diagrams.

Instructions

Search for images using Google Custom Search API. Returns image URLs, thumbnails, dimensions, and source page URLs.

When to use:

  • Finding visual content — photos, illustrations, graphics, diagrams

  • Need specific image formats, sizes, or color types

Key parameters:

  • size: huge, large, medium, small

  • type: clipart, face, lineart, photo, animated

  • color_type: color, gray, mono, trans (transparent)

  • file_type: jpg, gif, png, svg, webp

Caching: Results cached for 30 minutes.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesThe image search query
num_resultsNoNumber of image results to return
sizeNoFilter by image size
typeNoFilter by image type
color_typeNoFilter by color type
dominant_colorNoFilter by dominant color
file_typeNoFilter by file format
safeNoSafe search level

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
imagesYesList of image results
queryYesThe search query that was executed
resultCountYesNumber of images found
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Beyond the annotations (readOnlyHint, openWorldHint), the description adds valuable behavioral traits: caching for 30 minutes and the specific output fields. This provides useful operational context for the agent.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is highly concise and well-structured: a clear first sentence, followed by focused bullet points for usage and key parameters, and a caching note. No unnecessary text.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers purpose, usage scenarios, and caching, but lacks details on default parameters (e.g., num_results=5, safe search default) and does not clarify all available enum values. Despite the output schema existing, the incomplete parameter info reduces overall completeness.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Although schema description coverage is 100%, the description's 'Key parameters' list is incomplete and potentially misleading (e.g., omits 'icon', 'stock', 'dominant_color', 'safe', 'num_results'). This could cause the agent to incorrectly assume only listed values are valid, reducing reliability.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Search for images using Google Custom Search API' and specifies return types (URLs, thumbnails, dimensions, source pages). It distinctly differentiates from sibling tools like google_search and google_news_search by focusing on image content.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The 'When to use' section provides explicit scenarios (finding visual content, needing specific formats/sizes/colors). However, it does not mention when not to use or suggest alternative tools, which would strengthen guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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